From the point at which it was authored to the ways in which it has been transformed to the various platforms and data stores through which it has passed, your data has made quite the journey before ending up at the place in which you are consuming it. This begs the question: do you know where your data has been? Understanding each attribute of your data with a high degree of granularity can give you penetrating insights into the data’s usefulness, importance, and meaning, which is why tracking data lineage is essential to ensure you realize the full potential of the data you have at your disposal.
While documenting data lineage is not always simple — indeed, it can even be tedious and time-consuming — it empowers an organization to take control of its data in several valuable ways:
Firstly, understanding your data lineage enables you to see what data is redundant across your systems and data stores. Copying the same data from one system or data store to another introduces the risk that the data will become desynchronized, a risk that climbs higher each time the data is stored in duplicate. By documenting your data lineage at the attribute level, you can find and eliminate any duplicate data elements and lower the risk of introducing stale or incorrect data into your systems. Encouragingly, the rise of technologies like cloud computing and real-time processing has diminished the need for systems to store data multiple times. In today’s day and age, there can and should be a single source of truth for all master data.
Secondly, tracking your data lineage helps you understand what data elements are actually being used to drive your business. When documenting data lineage, organizations are often surprised by how many attributes are not being used despite the ample computing time, development effort, and testing resources that are dedicated to maintaining them. If an attribute of data is not used by the systems in your landscape, it is best to sunset the attribute entirely, as continuing to maintain extraneous data elements can cause confusion and lead to inaccurate conclusions.
Thirdly, documenting your data lineage helps your technical teams quickly analyze and identify how changes to specific data elements will affect the systems that utilize the elements. By documenting and governing the lineage of your data attributes, you lower the risk that an integration or communication between systems will be missed or forgotten when you make changes to data types or sizes and/or adjust how you compute or maintain a data element.
Finally, tracking your data lineage enables you to ensure end-users are able to use the data attributes at their disposal confidently and effectively, regardless of whether they are deriving insights from a custom system report or using ad hoc reports from a data lake or data warehouse. Having access to clearly documented data lineage helps end-users understand which attributes they need and how the attributes were captured, derived, and transformed.
In light of everything outlined above, it can be extremely beneficial to use a prescribed methodology and tool to manage the collection of the data lineage for a complex environment. The right methodology and tool enables you to efficiently and effectively clean up, extend, and modernize your data so that you can focus on the future data needs of your business while simultaneously reducing the risk of managing your complex environment.
